How Sure Are You? Science, Biostatistics and Cancer Education for Grades 9-12 is a curriculum development and dissemination project to create four web-based teaching modules that will make it possible for high school teachers or other educators to readily access and make use of cancer education resources they otherwise might not consider well matched to their curriculum. The modules will address national science, mathematics, and health education standards using learning experiences and instructional strategies supported by research on effectively teaching diverse learners. Designed to address issues of underrepresentation in clinical trials and STEM careers, specific aims for student learning are: (1) understanding of cancer, population studies, and clinical trials; (2) ability to design and present a valid scientific study; (3) ability to select and use appropriate statistical methods to analyze data; and (4) interest in science and STEM careers. The three-year development phase is an ongoing, iterative process of designing, piloting, evaluating, and revising modules. Each module will have six components: (1) 3-5 hands-on lessons with challenging problems and data sets, (2) an inquiry-based project, (3) suggestions for extension activities, (4) a performance-based assessment, (5) a profile of an NIH-supported cancer scientist or biostatistician from a STEM underrepresented group who is doing work related to the topic, and (6) links to other relevant resources. Modules will also serve as a professional development tool for teachers by providing the background and support necessary for effective teaching During the two-year dissemination phase, modules will undergo a national field test, be published via the SEPA website and promoted through national organizations of health education, science, and mathematics teachers (e.g., NSTA, NCTM, AAHE). The module topics selected from key mathematics, science inquiry, and health education standards are: (1) Characteristics of Distributions and Community Knowledge about Clinical Trials; (2) Randomization and Clinical Trials; (3) Causation vs Correlation in Cancer Risks and Screenings ; and (4) Designing and Analyzing Cancer Population Studies